code: def context_to_response_eval(
      self, data, eval_dial_list=None, same_eval_as_cambridge=False
  ):
      dials = self.pack_dial(data)
      counts = {}
      for req in self.requestables:
          counts[req + "_total"] = 0
          counts[req + "_offer"] = 0
  
      dial_num, successes, matches = 0, 0, 0
  
      for dial_id in dials:
          if eval_dial_list and dial_id + ".json" not in eval_dial_list:
              continue
          dial = dials[dial_id]
          reqs = {}
          goal = {}
          if (
              ".json" not in dial_id
              and ".json" in list(self.all_data.keys())[0]
          ):
              dial_id = dial_id + ".json"
          for domain in ontology.all_domains:
              if self.all_data[dial_id]["goal"].get(domain):
                  true_goal = self.all_data[dial_id]["goal"]
                  goal = self._parseGoal(goal, true_goal, domain)
          # print(goal)
          for domain in goal.keys():
              reqs[domain] = goal[domain]["requestable"]
  
          # print('\n',dial_id)
          (
              success,
              match,
              stats,
              counts,
          ) = self._evaluateGeneratedDialogue(
              dial,
              goal,
              reqs,
              counts,
              same_eval_as_cambridge=same_eval_as_cambridge,
          )
  
          successes += success
          matches += match
          dial_num += 1
  
          # for domain in gen_stats.keys():
          #     gen_stats[domain][0] += stats[domain][0]
          #     gen_stats[domain][1] += stats[domain][1]
          #     gen_stats[domain][2] += stats[domain][2]
  
          # if 'SNG' in filename:
          #     for domain in gen_stats.keys():
          #         sng_gen_stats[domain][0] += stats[domain][0]
          #         sng_gen_stats[domain][1] += stats[domain][1]
          #         sng_gen_stats[domain][2] += stats[domain][2]
  
      # self.logger.info(report)
      succ_rate = successes / (float(dial_num) + 1e-10) * 100
      match_rate = matches / (float(dial_num) + 1e-10) * 100
      return succ_rate, match_rate, counts, dial_num
  
imports: import math, logging, copy, json
  from collections import Counter, OrderedDict
  from nltk.util import ngrams
  from .None import ontology
  from .clean_dataset import clean_slot_values
label_desc: Use image node_id 16 for calling the MultiWozEvaluator obj's underlying member method code with example usage: obj.context_to_response_eval(data, eval_dial_list, same_eval_as_cambridge) and returns: succ_rate,  match_rate,  counts,  dial_num